• Korea Journal of Hospital Management
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• v.27 no.1
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• pp.1-10
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• 2022

Background: This study aims to empirically compare and evaluate the current status of medical accessibility and health inequality between people with disabilities and without. We calculated the ACSC hospitalization rate, which is a medical accessibility index, for hypertension, a major risk factor for cardiovascular disease that accounts for more than 20% of deaths among people with disabilities using the 2016 National Health Insurance Big Data. Methods: The subjects of the study were a total of 601,520, including 64,018 people with disabilities and 537,501 people without. Logistic regression was performed to analyze the differences in hypertension hospitalization rates adjusted for demographic and sociological characteristics and disease characteristics using SAS 9.4 program. Results: Before adjusting for the characteristics, the hypertension hospitalization rate of people with disabilities was 1.55%, and the people without disabilities were 0.49%. After adjusting, it was found that people with disabilities were 2.11 times higher than people without disabilities, and it was statistically significant. Conclusion: The preventable hospitalization rate of people with disabilities is higher than that of people without, suggesting that the disabled have problems with access to medical care and health inequality. Therefore, the government's policy improvement is required to close the medical gap for the disabled.

• Korean Chemical Engineering Research
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• v.60 no.1
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• pp.34-50
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• 2022

Since the Paris climate agreement, reducing greenhouse gases has been the most important global issue. In particular, it is necessary to reduce fossil fuels in the mobility sector, which accounts for a significant portion of total greenhouse gas emissions. In this paper, we investigated the economic feasibility of green mobility energy supply chains, which supply hydrogen as fuel to hydrogen vehicles based on electricity from renewable energy sources. The design and operation costs were analyzed by evaluating nine scenarios representing various combinatorial possibilities such as renewable energy generation, hydrogen production through water electrolytes, hydrogen storage and hydrogen refueling stations. Simulation calculations were made using Homer Pro, widely used commercial software in the field. The experience gained in this study could be further utilized to construct actual hydrogen energy systems.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.25-31
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• 2022

The purpose of this study is to explore the implications for the systematic operation of the AI curriculum by analyzing the current status of the AI major curriculum in universities. To this end, This study analyzed the relevant curriculum of domestic universities(a total of 51 schools) and overseas QS Top 10 universities based on the industry demand-based standard of AI major curriculum developed through prior research. The main research results are as follows. First, in the case of domestic universities, Python-centered programming subjects were lacking. Second, there were few subjects for advanced learning such as AI application and convergence. Third, the subjects required to perform the AI developer job were insufficient. Fourth, in the case of colleges, the ratio of AI mathematics-related subjects was low. Based on these results, this study presented implications for the systematic operation of the AI major education.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1762-1769
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• 2021

The final goal of this study is to develop a system that can analyze whether a wanted vehicle is a criminal vehicle from images collected from black boxes, smartphones, CCTVs, and so on. Data collection was collected using a self-developed black box. The used data in this study has used a total of 83,753 cases such as the eight vehicle types(truck, RV, passenger car, van, SUV, bus, sports car, electric vehicle) and 434 vehicle models. As a result of vehicle recognition using YOLO v5, mAP was found to be 80%. As a result of identifying the vehicle model with ReXNet using the self-developed black box, the accuracy was found to be 99%. The result was verified by surveying field police officers. These results suggest that improving the accuracy of data labeling helps to improve vehicle recognition performance.

• Korean Journal of Veterinary Service
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• v.44 no.4
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• pp.217-225
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• 2021

We investigated the effect of temperature and stock density on the collection efficiency of oral fluid in the pig farm in Korea. Three pig farms with similar breeding environmental conditions were selected and four pens of each farm (total 12 pens) were tested for the collection efficiency of oral fluid from pigs. Collection rate was considered as significant when oral fluid was collected from 70% of pigs within a pen. In the case of growing pigs, when internal temperature of pig barn increased by one designated degree (5℃), the oral fluid collection rate significantly decreased by 24.7% (P<0.05). The collection rate of oral fluid also decreased by 7.1% (P<0.05) as the density rate increase by one designated degree (12.5%). It was estimated that the collection efficiency of oral fluid decreased when the internal temperature of pig barn was 30℃ or higher, or barn density is higher 25% or high. On the other hand, in the case of stall-housing sows, unlike growing pigs, there was no significant differences according to the temperature, so oral fluid collection was considered to be efficient even in hot season.

• The Journal of Advanced Prosthodontics
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• v.14 no.2
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• pp.70-77
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• 2022

PURPOSE. This study evaluated screw loosening and 3D crown displacement after cyclic loading of implant-supported incisor crowns cemented with original titanium bases or with three compatible, nonoriginal components. MATERIALS AND METHODS. A total of 32 dental implants were divided into four groups (n = 8 each): Group 1 used original titanium bases, while Groups 2-4 used compatible components. The reverse torque value (RTV) was evaluated prior to and after cyclic loading (1,200,000 cycles). Samples (prior to and after cyclic loading) were scanned with a microcomputed tomography (micro-CT). Preload and postload files were superimposed by 3D inspection software, and 3D crown displacement analysis was performed using root-mean-square (RMS) values. All datasets were analyzed using one-way ANOVA and Tukey's post hoc analysis. RESULTS. Significant variations were observed in the postload RTV, depending on the titanium base brand (P < .001). The mean postload RTVs were significantly higher in Groups 1 and 2 than in the other study groups. While evaluating 3D crown displacement, the lowest mean RMS value was shown in the original Group 1, with the highest RMS value occurring in Group 4. CONCLUSION. Within the limitations of this in vitro study and under the implemented conditions, it was concluded that the manufacturer brand of the titanium base significantly influenced screw loosening following the fatigue test and influenced 3D crown displacement after cyclic loading.

• Journal of Korean Dental Science
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• v.15 no.1
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• pp.9-18
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• 2022

Purpose: The purpose of this study was to evaluate whether three-dimensional (3D)-printed flexible denture resin has suitable mechanical properties for use as a thermoplastic denture base resin material. Materials and Methods: A total of 96 specimens were prepared using the 3D printed flexible denture resin (Flexible Denture). Specimens were designed in CAD software (Tinkercad) and printed through a digital light-processing 3D printer (Asiga MAX UV). Post-polymerization process was conducted according to air exposure or glycerin immersion at 35℃ or 60℃ and for 30 or 60 minutes. The maximum flexural strength, elastic modulus, 0.2% offset yield strength, and Vickers hardness of 3D-printed flexible denture resin were assessed. Result: The maximum flexural strength ranged from 64.46±2.03 to 84.25±4.32 MPa, the 0.2% offset yield strength ranged from 35.28±1.05 to 46.13±2.33 MPa, the elastic modulus ranged from 1,764.70±64.66 to 2,179.16±140.01 MPa, and the Vickers hardness ranged from 7.01±0.40 to 11.45±0.69 kg/mm². Conclusion: Within the limits of the present study, the maximum flexural strength, 0.2% offset yield strength, elastic modulus, and Vickers hardness are sufficient for clinical use under the post-polymerization conditions of 60℃ at 60 minutes with or without glycerin precipitation.

• Journal of KIBIM
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• v.12 no.2
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• pp.49-59
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• 2022

The main idea of this study is to propose a BIM-based automation system drawing up a report of energy conservation plan in the architecture division. In order to obtain a building permit, an energy conservation plan must be prepared for buildings with a total floor area of 500m² or more under the current law. Currently, it is adopted as a general method to complete a report by obtaining data and drawings necessary for an energy conservation plan through manual work and input them directly into the verification system. This method takes a lot of effort and time in the design phase which ultimately increases the initial cost of the business, including the services of companies specialized in the environmental field. However, in preparation for mandatory BIM work process in the future, it is necessary to introduce BIM-based automatic creation system that has an advantage for shortening the whole process to enable rapid permission of energy-saving designs for buildings. There may be many methods of automation, but this study introduces how to build an application using Dynamo of Revit, in terms of utilizing BIM, and write an energy conservation plan by automatic completion of report through Dynamo and Excel's VBA algorithm, which can save time and cost in preparing the report of energy conservation plan compared with the manual process. Also we have insisted that the digital transformation of architectural process is a necessary for an efficient use of our automation system in the current energy conservation plan workflow.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.63-68
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• 2022

Currently, there are a total of 68 emergency rooms based on Seoul, South Korea, and there is a portal site that allows you to inquire the location of the emergency room, but it is difficult to use in an actual emergency situation because it consists of selecting a gu and a self-governing dong. In addition, it may be more efficient to go to the emergency room directly because you may miss the golden time necessary for survival in a situation where you call 119 and wait for the rescue team. Therefore, in this paper, we propose a service that can quickly search the location of the emergency room based on a specific location through various functions supported by MongoDB. After downloading emergency room location data based on Seoul Metropolitan City, storing it in MongoDB, processing the data through various processing techniques, and applying a spatial index, you can query the emergency room based on distance from a specific location in real time.

• Journal of IKEEE
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• v.26 no.3
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• pp.468-474
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• 2022

In this paper, we propose a method to implement a real-time fire alarm system using deep learning. The deep learning image dataset for fire alarms acquired 1,500 sheets through the Internet. If various images acquired in a daily environment are learned as they are, there is a disadvantage that the learning accuracy is not high. In this paper, we propose a fire image data expansion method to improve learning accuracy. The data augmentation method learned a total of 2,100 sheets by adding 600 pieces of learning data using brightness control, blurring, and flame photo synthesis. The expanded data using the flame image synthesis method had a great influence on the accuracy improvement. A real-time fire detection system is a system that detects fires by applying deep learning to image data and transmits notifications to users. An app was developed to detect fires by analyzing images in real time using a model custom-learned from the YOLO V4 TINY model suitable for the Edge AI system and to inform users of the results. Approximately 10% accuracy improvement can be obtained compared to conventional methods when using the proposed data.